23 citations · 29 across the 4 of their papers we have counts for
5 papers
Staining normalization in histopathology: Method benchmarking using multicenter dataset
Umair Khan, Jouni Härkönen, Marjukka Friman +3
Hematoxylin and Eosin (H&E) has been the gold standard in tissue analysis for decades, however, tissue specimens stained in different laboratories vary, often significantly, in app…
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…
ACROBAT -- a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology
Philippe Weitz, Masi Valkonen, Leslie Solorzano +15
The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is an essential part of the pathologic assessment of surgically resecte…
Deformation equivariant cross-modality image synthesis with paired non-aligned training data
Joel Honkamaa, Umair Khan, Sonja Koivukoski +4
Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications. Recently, methods allowing training with paired but misaligned da…
Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration
Kaisa Liimatainen, Leena Latonen, Masi Valkonen +2
Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualizat…